DNA microarray analysis has become a widely used genetic tool; however, its massive scale creates quality control and analysis problems for most laboratories wishing to use it. The purpose of this proposal is to facilitate the application of this technology to fundamental hypothesis-driven research through the identification and resolution of the sources of cDNA microarray data variability. Since the array itself is a considerable source of variability we have developed a three-color array platform that allows prehybridization array visualization. Our direct labeling approach separates assessment of slide coating, printing and blocking from hybridization, enabling evaluation of element/array morphology, surface DNA deposition/retention, and background levels prior to hybridization. We have also developed Matarray, a software package for hybridized image processing and data acquisition that provides quantitative QC for each array element as well as the entire slide. Combined, these efforts provide the basis for an integrated quality control (QC) approach to effectively manage microarray technical and systematic variability. For this application we will build upon these initial efforts through the following specific aims 1) We will study the relationship between measurable prehybridization image quality parameters and data quality/reproducibility, including the influence of background, spot morphology, and bound probe. Data compression caused by limiting bound probe will be quantified using the third dye so that data derived from sub-optimal spots can either be normalized or filtered. 2) We will develop pre-hybridization array qualification software based upon parameters identified in aim 1, which will encompass probe plate tracking, quantification of probe available for hybridization, and array/element morphology. Post-hybridization algorithms will be developed that utilize third dye information for data normalization and filtering. 3) Our improved microarray and analysis platforms will be validated by expression profiling disease development in an animal system. The commercial oligonucleotide and cDNA arrays will be used as reference platforms to assess cost effectiveness and value of our approach. Our success will provide an accurate, flexible, lower cost alternative to commercial arrays for laboratories wishing to conduct gene expression studies.